Samples and data are analyzed from a longitudinal population study conducted from 1965 to 2007 that allows study of the risk factors and effects of diabetes mellitus. Risk factors for obesity, hypertension, and nephropathy are also studied, along with the relationships of these diseases to diabetes and their effects on development of vascular complications and mortality. The genetics of diabetes is studied by means of family studies and relationships of genetic markers to disease. These findings are reported in DK069028 (Genetic epidemiology of diabetes and obesity) and DK069094 (Genetic epidemiology of diabetic complications). Findings related to kidney complications of diabetes are reported in DK069062 (Epidemiology, pathophysiology and treatment of diabetic nephropathy). Other findings published this fiscal year are summarized here. Environmental contaminants and risk of diabetes. Relationships were examined between persistent organic pollutants (POPs) and incident type 2 diabetes, end-stage renal disease (ESRD) and mortality. Most POPs were positively but not significantly associated with incident diabetes. Among participants with diabetes, low-chlorine PCBs increased the risk of ESRD and death without ESRD, whereas several PSTs predicted death without ESRD. Comparison of 1- and 2-hour post-load plasma glucose in predicting diabetes. Elevated 2-h plasma glucose concentration (2 h-PG) during a 75 g OGTT predict the development of type 2 diabetes mellitus. However, 1-h plasma glucose concentration (1 h-PG) is associated with insulin secretion and may be a better predictor of type 2 diabetes. We investigated the associations of 1 h-PG and 2 h-PG with insulin secretion and action and compared 1 h-PG and 2 h-PG as predictors of type 2 diabetes mellitus. The 1 h-PG was associated with important physiological predictors of type 2 diabetes and was as effective as 2 h-PG for predicting type 2 diabetes mellitus. The 1 h-PG is, therefore, an alternative method of identifying individuals with an elevated risk of type 2 diabetes mellitus. HbA1c in predicting diabetes in children and adults. HbA1c, fasting plasma glucose (FPG), and 2-h postload plasma glucose (2hPG) concentrations were measured in this longitudinal study to determine their utility in predicting incident diabetes. HbA1c was a useful predictor of diabetes risk in children and can be used to identify prediabetes in children with other type 2 diabetes risk factors with the same predictive value as FPG and 2hPG. Obesity and cardiometabolic risk factors in youth. We studied the relationship between body mass index (BMI) and cardiometabolic risk factors in American Indian children and adolescents. Higher BMI was associated with blood pressure elevation, hyperglycemia and dyslipidemia, thus confirming adverse health effects of obesity at young ages. Preventing diabetes. Knowledge of diabetes risk factors coming from this and other studies led to the hypothesis that type 2 diabetes could be prevented or delayed in adults at high short-term risk. This hypothesis was confirmed in the Diabetes Prevention Program (DPP), a multicenter randomized clinical trial in which many of the participants and investigators in this project participated. We are now in a long-term follow-up phase, the Diabetes Prevention Program Outcomes Study (DPPOS), to assess long-term success with weight loss, reduction in the incidence of diabetes, and effects on diabetes complications. This study is reported in DK075078 (Prevention of type 2 diabetes). Accounting for blood pressure treatment in epidemiologic studies of blood pressure. Underlying blood pressure is that observed in the absence of antihypertensive treatment or, among those treated, the estimate of that which would be observed without treatment. We examined the relationships between diabetes or obesity and underlying systolic blood pressure adjusted for antihypertensive treatment by several methods. Data from two population studies were analyzedan American Indian community in Arizona and the National Health and Nutrition Examination Surveys. The common methods of ignoring antihypertensive treatment or including it as a covariate in a regression model underestimated the effects of diabetes and obesity on underlying blood pressure, compared to the recommended method of the censored normal regression. Proper accounting for antihypertensive treatment is needed in interpreting variables that affect blood pressure.